Pandas Profiling Report

Dataset statistics

Number of variables	24
Number of observations	65628
Missing cells	4
Missing cells (%)	< 0.1%
Duplicate rows	7399
Duplicate rows (%)	11.3%
Total size in memory	12.0 MiB
Average record size in memory	192.0 B

Variable types

Unsupported	1
Categorical	12
Numeric	11

Alerts

`targetRelease` has constant value "AIR"	Constant
`CONTINENT` has constant value "EUROPE"	Constant
Dataset has 7399 (11.3%) duplicate rows	Duplicates
`EPRTRAnnexIMainActivityLabel` has a high cardinality: 71 distinct values	High cardinality
`FacilityInspireID` has a high cardinality: 7185 distinct values	High cardinality
`facilityName` has a high cardinality: 7930 distinct values	High cardinality
`City` has a high cardinality: 5136 distinct values	High cardinality
`REPORTER NAME` has a high cardinality: 45016 distinct values	High cardinality
`CITY ID` has a high cardinality: 5136 distinct values	High cardinality
`EPRTRAnnexIMainActivityCode` has a high cardinality: 70 distinct values	High cardinality
`max_wind_speed` is highly correlated with `avg_wind_speed` and 1 other fields	High correlation
`avg_wind_speed` is highly correlated with `max_wind_speed` and 1 other fields	High correlation
`min_wind_speed` is highly correlated with `max_wind_speed` and 1 other fields	High correlation
`max_temp` is highly correlated with `avg_temp` and 1 other fields	High correlation
`avg_temp` is highly correlated with `max_temp` and 1 other fields	High correlation
`min_temp` is highly correlated with `max_temp` and 1 other fields	High correlation
`max_wind_speed` is highly correlated with `avg_wind_speed` and 1 other fields	High correlation
`avg_wind_speed` is highly correlated with `max_wind_speed` and 1 other fields	High correlation
`min_wind_speed` is highly correlated with `max_wind_speed` and 1 other fields	High correlation
`max_temp` is highly correlated with `avg_temp` and 1 other fields	High correlation
`avg_temp` is highly correlated with `max_temp` and 1 other fields	High correlation
`min_temp` is highly correlated with `max_temp` and 1 other fields	High correlation
`max_wind_speed` is highly correlated with `avg_wind_speed`	High correlation
`avg_wind_speed` is highly correlated with `max_wind_speed` and 1 other fields	High correlation
`min_wind_speed` is highly correlated with `avg_wind_speed`	High correlation
`max_temp` is highly correlated with `avg_temp` and 1 other fields	High correlation
`avg_temp` is highly correlated with `max_temp` and 1 other fields	High correlation
`min_temp` is highly correlated with `max_temp` and 1 other fields	High correlation
`EPRTRAnnexIMainActivityCode` is highly correlated with `pollutant` and 4 other fields	High correlation
`pollutant` is highly correlated with `EPRTRAnnexIMainActivityCode` and 3 other fields	High correlation
`CONTINENT` is highly correlated with `EPRTRAnnexIMainActivityCode` and 5 other fields	High correlation
`countryName` is highly correlated with `CONTINENT` and 1 other fields	High correlation
`targetRelease` is highly correlated with `EPRTRAnnexIMainActivityCode` and 5 other fields	High correlation
`EPRTRAnnexIMainActivityLabel` is highly correlated with `EPRTRAnnexIMainActivityCode` and 4 other fields	High correlation
`eprtrSectorName` is highly correlated with `EPRTRAnnexIMainActivityCode` and 3 other fields	High correlation
`countryName` is highly correlated with `EPRTRAnnexIMainActivityLabel` and 2 other fields	High correlation
`eprtrSectorName` is highly correlated with `EPRTRAnnexIMainActivityLabel` and 3 other fields	High correlation
`EPRTRAnnexIMainActivityLabel` is highly correlated with `countryName` and 4 other fields	High correlation
`pollutant` is highly correlated with `eprtrSectorName` and 3 other fields	High correlation
`MONTH` is highly correlated with `max_temp` and 2 other fields	High correlation
`max_wind_speed` is highly correlated with `avg_wind_speed` and 1 other fields	High correlation
`avg_wind_speed` is highly correlated with `max_wind_speed` and 1 other fields	High correlation
`min_wind_speed` is highly correlated with `max_wind_speed` and 1 other fields	High correlation
`max_temp` is highly correlated with `MONTH` and 2 other fields	High correlation
`avg_temp` is highly correlated with `MONTH` and 2 other fields	High correlation
`min_temp` is highly correlated with `MONTH` and 2 other fields	High correlation
`DAY WITH FOGS` is highly correlated with `countryName`	High correlation
`EPRTRAnnexIMainActivityCode` is highly correlated with `countryName` and 4 other fields	High correlation
`EPRTRSectorCode` is highly correlated with `eprtrSectorName` and 3 other fields	High correlation
`REPORTER NAME` is uniformly distributed	Uniform
`df_index` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`DAY WITH FOGS` has 18771 (28.6%) zeros	Zeros

Reproduction

Analysis started	2022-05-21 11:42:05.088624
Analysis finished	2022-05-21 11:42:53.798946
Duration	48.71 seconds
Software version	pandas-profiling v3.2.0
Download configuration	config.json

df_index
Unsupported

REJECTED
UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	512.8 KiB

countryName
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	32
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	512.8 KiB

United Kingdom	9016
Germany	8768
France	7365
Spain	7017
Italy	6280
Other values (27)	27182

Length

Max length	14
Median length	11
Mean length	7.585222771
Min length	5

Characters and Unicode

Total characters	497803
Distinct characters	41
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Germany
2nd row	Italy
3rd row	Spain
4th row	Czechia
5th row	Finland

Common Values

Value	Count	Frequency (%)
United Kingdom	9016	13.7%
Germany	8768	13.4%
France	7365	11.2%
Spain	7017	10.7%
Italy	6280	9.6%
Poland	4252	6.5%
Netherlands	2347	3.6%
Finland	2271	3.5%
Sweden	2091	3.2%
Belgium	1875	2.9%
Other values (22)	14346	21.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
united	9016	12.1%
kingdom	9016	12.1%
germany	8768	11.7%
france	7365	9.9%
spain	7017	9.4%
italy	6280	8.4%
poland	4252	5.7%
netherlands	2347	3.1%
finland	2271	3.0%
sweden	2091	2.8%
Other values (23)	16221	21.7%

Most occurring characters

Value	Count	Frequency (%)
n	61582	12.4%
a	54544	11.0%
e	44796	9.0%
i	37527	7.5%
d	31510	6.3%
r	27901	5.6%
m	22719	4.6%
l	22193	4.5%
t	21920	4.4%
o	17878	3.6%
Other values (31)	155233	31.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	414143	83.2%
Uppercase Letter	74644	15.0%
Space Separator	9016	1.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	61582	14.9%
a	54544	13.2%
e	44796	10.8%
i	37527	9.1%
d	31510	7.6%
r	27901	6.7%
m	22719	5.5%
l	22193	5.4%
t	21920	5.3%
o	17878	4.3%
Other values (13)	71573	17.3%

Uppercase Letter

Value	Count	Frequency (%)
S	10815	14.5%
G	9705	13.0%
F	9636	12.9%
U	9016	12.1%
K	9016	12.1%
I	7706	10.3%
P	5465	7.3%
B	2724	3.6%
N	2711	3.6%
C	2116	2.8%
Other values (7)	5734	7.7%

Space Separator

Value	Count	Frequency (%)
	9016	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	488787	98.2%
Common	9016	1.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	61582	12.6%
a	54544	11.2%
e	44796	9.2%
i	37527	7.7%
d	31510	6.4%
r	27901	5.7%
m	22719	4.6%
l	22193	4.5%
t	21920	4.5%
o	17878	3.7%
Other values (30)	146217	29.9%

Common

Value	Count	Frequency (%)
	9016	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	497803	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	61582	12.4%
a	54544	11.0%
e	44796	9.0%
i	37527	7.5%
d	31510	6.3%
r	27901	5.6%
m	22719	4.6%
l	22193	4.5%
t	21920	4.4%
o	17878	3.6%
Other values (31)	155233	31.2%

eprtrSectorName
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	512.8 KiB

Energy sector	24562
Waste and wastewater management	15889
Mineral industry	10188
Chemical industry	4334
Paper and wood production and processing	3817
Other values (4)	6838

Length

Max length	63
Median length	46
Mean length	22.79850064
Min length	13

Characters and Unicode

Total characters	1496220
Distinct characters	32
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Mineral industry
2nd row	Mineral industry
3rd row	Waste and wastewater management
4th row	Energy sector
5th row	Waste and wastewater management

Common Values

Value	Count	Frequency (%)
Energy sector	24562	37.4%
Waste and wastewater management	15889	24.2%
Mineral industry	10188	15.5%
Chemical industry	4334	6.6%
Paper and wood production and processing	3817	5.8%
Production and processing of metals	3154	4.8%
Intensive livestock production and aquaculture	2144	3.3%
Animal and vegetable products from the food and beverage sector	1305	2.0%
Other activities	235	0.4%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
and	31431	15.4%
sector	25867	12.6%
energy	24562	12.0%
waste	15889	7.8%
wastewater	15889	7.8%
management	15889	7.8%
industry	14522	7.1%
mineral	10188	5.0%
production	9115	4.5%
processing	6971	3.4%
Other values (17)	34313	16.8%

Most occurring characters

Value	Count	Frequency (%)
e	176519	11.8%
a	140807	9.4%
	139008	9.3%
n	134160	9.0%
t	127266	8.5%
r	117225	7.8%
s	95091	6.4%
o	69220	4.6%
d	61495	4.1%
c	52115	3.5%
Other values (22)	383314	25.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1291584	86.3%
Space Separator	139008	9.3%
Uppercase Letter	65628	4.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	176519	13.7%
a	140807	10.9%
n	134160	10.4%
t	127266	9.9%
r	117225	9.1%
s	95091	7.4%
o	69220	5.4%
d	61495	4.8%
c	52115	4.0%
i	51428	4.0%
Other values (13)	266258	20.6%

Uppercase Letter

Value	Count	Frequency (%)
E	24562	37.4%
W	15889	24.2%
M	10188	15.5%
P	6971	10.6%
C	4334	6.6%
I	2144	3.3%
A	1305	2.0%
O	235	0.4%

Space Separator

Value	Count	Frequency (%)
	139008	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1357212	90.7%
Common	139008	9.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	176519	13.0%
a	140807	10.4%
n	134160	9.9%
t	127266	9.4%
r	117225	8.6%
s	95091	7.0%
o	69220	5.1%
d	61495	4.5%
c	52115	3.8%
i	51428	3.8%
Other values (21)	331886	24.5%

Common

Value	Count	Frequency (%)
	139008	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1496220	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	176519	11.8%
a	140807	9.4%
	139008	9.3%
n	134160	9.0%
t	127266	8.5%
r	117225	7.8%
s	95091	6.4%
o	69220	4.6%
d	61495	4.1%
c	52115	3.5%
Other values (22)	383314	25.6%

EPRTRAnnexIMainActivityLabel
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct	71
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	512.8 KiB

Thermal power stations and other combustion installations	21527
Landfills (excluding landfills of inert waste and landfills, which were definitely closed before 16.7.2001 or for which the after-care phase required by the competent authorities according to Article 13 of Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste has expired)	10452
Installations for the incineration of non-hazardous waste in the scope of Directive 2000/76/EC of the European Parliament and of the Council of 4 December 2000 on the incineration of waste	3454
Installations for the production of cement clinker in rotary kilns	3300
Installations for the manufacture of glass, including glass fibre	2725
Other values (66)	24170

Length

Max length	289
Median length	276
Mean length	126.407768
Min length	10

Characters and Unicode

Total characters	8295889
Distinct characters	62
Distinct categories	8 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Installations for the production of cement clinker in rotary kilns
2nd row	Installations for the production of cement clinker in rotary kilns, lime in rotary kilns, cement or lime in other furnaces. Note to reporters, use Level 3 activity e.g. 3(c)(i), in preference to 3(c). Level 2 activity class (i.e. 3(c)) only to be used where Level 3 is not available.
3rd row	Landfills (excluding landfills of inert waste and landfills, which were definitely closed before 16.7.2001 or for which the after-care phase required by the competent authorities according to Article 13 of Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste has expired)
4th row	Thermal power stations and other combustion installations
5th row	Urban waste-water treatment plants

Common Values

Value	Count	Frequency (%)
Thermal power stations and other combustion installations	21527	32.8%
Landfills (excluding landfills of inert waste and landfills, which were definitely closed before 16.7.2001 or for which the after-care phase required by the competent authorities according to Article 13 of Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste has expired)	10452	15.9%
Installations for the incineration of non-hazardous waste in the scope of Directive 2000/76/EC of the European Parliament and of the Council of 4 December 2000 on the incineration of waste	3454	5.3%
Installations for the production of cement clinker in rotary kilns	3300	5.0%
Installations for the manufacture of glass, including glass fibre	2725	4.2%
Mineral oil and gas refineries	2454	3.7%
Industrial plants for the production of paper and board and other primary wood products (such as chipboard, fibreboard and plywood)	2416	3.7%
Installations for the production of cement clinker in rotary kilns, lime in rotary kilns, cement or lime in other furnaces. Note to reporters, use Level 3 activity e.g. 3(c)(i), in preference to 3(c). Level 2 activity class (i.e. 3(c)) only to be used where Level 3 is not available.	1519	2.3%
Installations for the production of pig iron or steel (primary or secondary melting) including continuous casting	1461	2.2%
Industrial plants for the production of pulp from timber or similar fibrous materials	1395	2.1%
Other values (61)	14925	22.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
of	88111	7.2%
the	73814	6.0%
and	49729	4.1%
installations	44851	3.7%
for	41088	3.3%
landfills	31356	2.6%
waste	29457	2.4%
other	26424	2.2%
or	23527	1.9%
to	22347	1.8%
Other values (348)	796131	64.9%

Most occurring characters

Value	Count	Frequency (%)
	1161207	14.0%
e	657681	7.9%
o	579699	7.0%
i	573175	6.9%
t	542074	6.5%
n	506849	6.1%
a	505255	6.1%
r	472130	5.7%
l	420141	5.1%
s	411562	5.0%
Other values (52)	2466116	29.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	6458304	77.8%
Space Separator	1161207	14.0%
Decimal Number	291000	3.5%
Uppercase Letter	170941	2.1%
Other Punctuation	122715	1.5%
Open Punctuation	37186	0.4%
Close Punctuation	37186	0.4%
Dash Punctuation	17350	0.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	657681	10.2%
o	579699	9.0%
i	573175	8.9%
t	542074	8.4%
n	506849	7.8%
a	505255	7.8%
r	472130	7.3%
l	420141	6.5%
s	411562	6.4%
c	288178	4.5%
Other values (16)	1501560	23.3%

Uppercase Letter

Value	Count	Frequency (%)
C	32279	18.9%
I	23523	13.8%
T	22803	13.3%
L	22347	13.1%
A	20995	12.3%
D	17433	10.2%
E	17360	10.2%
N	4404	2.6%
P	3491	2.0%
M	2642	1.5%
Other values (8)	3664	2.1%

Decimal Number

Value	Count	Frequency (%)
1	62805	21.6%
9	62712	21.6%
0	47668	16.4%
3	34627	11.9%
2	33896	11.6%
6	24448	8.4%
7	15500	5.3%
4	7960	2.7%
8	1017	0.3%
5	367	0.1%

Other Punctuation

Value	Count	Frequency (%)
.	48909	39.9%
,	43554	35.5%
/	28017	22.8%
:	2235	1.8%

Space Separator

Value	Count	Frequency (%)
	1161207	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	37186	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	37186	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	17350	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6629245	79.9%
Common	1666644	20.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	657681	9.9%
o	579699	8.7%
i	573175	8.6%
t	542074	8.2%
n	506849	7.6%
a	505255	7.6%
r	472130	7.1%
l	420141	6.3%
s	411562	6.2%
c	288178	4.3%
Other values (34)	1672501	25.2%

Common

Value	Count	Frequency (%)
	1161207	69.7%
1	62805	3.8%
9	62712	3.8%
.	48909	2.9%
0	47668	2.9%
,	43554	2.6%
(	37186	2.2%
)	37186	2.2%
3	34627	2.1%
2	33896	2.0%
Other values (8)	96894	5.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	8295889	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	1161207	14.0%
e	657681	7.9%
o	579699	7.0%
i	573175	6.9%
t	542074	6.5%
n	506849	6.1%
a	505255	6.1%
r	472130	5.7%
l	420141	5.1%
s	411562	5.0%
Other values (52)	2466116	29.7%

FacilityInspireID
Categorical

HIGH CARDINALITY

Distinct	7185
Distinct (%)	10.9%
Missing	0
Missing (%)	0.0%
Memory size	512.8 KiB

https://data.ied_registry.omgeving.vlaanderen.be/id/productionfacility//BE.VL.000000067.FACILITY	42
UK.CAED/BEISOffsh-Foinaven-FPSO.FACILITY	41
ES.CAED/003486000.FACILITY	38
UK.CAED/BEISOffsh-Alba-Northern.FACILITY	38
UK.CAED/BEISOffsh-Nelson.FACILITY	38
Other values (7180)	65431

Length

Max length	96
Median length	85
Mean length	33.13148351
Min length	17

Characters and Unicode

Total characters	2174353
Distinct characters	67
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1033 ?
Unique (%)	1.6%

Sample

1st row	https://registry.gdi-de.org/id/de.ni.mu/06221720040
2nd row	IT.CAED/240602021.FACILITY
3rd row	ES.CAED/001966000.FACILITY
4th row	CZ.MZP.U422/CZ34736841.FACILITY
5th row	http://paikkatiedot.fi/so/1002031/pf/ProductionFacility/0000000928.ProductionFacility

Common Values

Value	Count	Frequency (%)
https://data.ied_registry.omgeving.vlaanderen.be/id/productionfacility//BE.VL.000000067.FACILITY	42	0.1%
UK.CAED/BEISOffsh-Foinaven-FPSO.FACILITY	41	0.1%
ES.CAED/003486000.FACILITY	38	0.1%
UK.CAED/BEISOffsh-Alba-Northern.FACILITY	38	0.1%
UK.CAED/BEISOffsh-Nelson.FACILITY	38	0.1%
NL.RIVM/000000062.FACILITY	38	0.1%
FR.CAED/11416.FACILITY	37	0.1%
FR.CAED/11428.FACILITY	37	0.1%
FR.CAED/6705.FACILITY	37	0.1%
SE.CAED/10019434.Facility	36	0.1%
Other values (7175)	65246	99.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
https://data.ied_registry.omgeving.vlaanderen.be/id/productionfacility//be.vl.000000067.facility	42	0.1%
uk.caed/beisoffsh-foinaven-fpso.facility	41	0.1%
es.caed/003486000.facility	38	0.1%
uk.caed/beisoffsh-alba-northern.facility	38	0.1%
uk.caed/beisoffsh-nelson.facility	38	0.1%
nl.rivm/000000062.facility	38	0.1%
fr.caed/11416.facility	37	0.1%
fr.caed/11428.facility	37	0.1%
fr.caed/6705.facility	37	0.1%
se.caed/10019434.facility	36	0.1%
Other values (7150)	65246	99.4%

Most occurring characters

Value	Count	Frequency (%)
0	207699	9.6%
.	166479	7.7%
I	116275	5.3%
/	115391	5.3%
A	105738	4.9%
C	93135	4.3%
E	80103	3.7%
i	71010	3.3%
1	67342	3.1%
F	66990	3.1%
Other values (57)	1084191	49.9%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	787373	36.2%
Lowercase Letter	536686	24.7%
Decimal Number	520271	23.9%
Other Punctuation	292521	13.5%
Dash Punctuation	31291	1.4%
Connector Punctuation	6211	0.3%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
I	116275	14.8%
A	105738	13.4%
C	93135	11.8%
E	80103	10.2%
F	66990	8.5%
T	62224	7.9%
L	60118	7.6%
Y	50945	6.5%
D	38767	4.9%
P	16099	2.0%
Other values (17)	96979	12.3%

Lowercase Letter

Value	Count	Frequency (%)
i	71010	13.2%
t	51922	9.7%
e	50987	9.5%
r	44789	8.3%
d	44178	8.2%
g	29880	5.6%
p	28924	5.4%
s	28721	5.4%
o	24364	4.5%
a	23573	4.4%
Other values (15)	138338	25.8%

Decimal Number

Value	Count	Frequency (%)
0	207699	39.9%
1	67342	12.9%
2	45610	8.8%
3	33167	6.4%
4	30352	5.8%
7	29060	5.6%
5	29057	5.6%
6	28379	5.5%
9	25596	4.9%
8	24009	4.6%

Other Punctuation

Value	Count	Frequency (%)
.	166479	56.9%
/	115391	39.4%
:	10651	3.6%

Dash Punctuation

Value	Count	Frequency (%)
-	31291	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	6211	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1324059	60.9%
Common	850294	39.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
I	116275	8.8%
A	105738	8.0%
C	93135	7.0%
E	80103	6.0%
i	71010	5.4%
F	66990	5.1%
T	62224	4.7%
L	60118	4.5%
t	51922	3.9%
e	50987	3.9%
Other values (42)	565557	42.7%

Common

Value	Count	Frequency (%)
0	207699	24.4%
.	166479	19.6%
/	115391	13.6%
1	67342	7.9%
2	45610	5.4%
3	33167	3.9%
-	31291	3.7%
4	30352	3.6%
7	29060	3.4%
5	29057	3.4%
Other values (5)	94846	11.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2170642	99.8%
None	3711	0.2%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	207699	9.6%
.	166479	7.7%
I	116275	5.4%
/	115391	5.3%
A	105738	4.9%
C	93135	4.3%
E	80103	3.7%
i	71010	3.3%
1	67342	3.1%
F	66990	3.1%
Other values (56)	1080480	49.8%

None

Value	Count	Frequency (%)
Ś	3711	100.0%

facilityName
Categorical

HIGH CARDINALITY

Distinct	7930
Distinct (%)	12.1%
Missing	0
Missing (%)	0.0%
Memory size	512.8 KiB

Enel Produzione S.p.A.	234
SNAM Rete Gas	123
A2A gencogas S.p.A.	112
Trans Austria Gasleitung GmbH	109
Versalis S.p.A.	102
Other values (7925)	64948

Length

Max length	152
Median length	104
Mean length	30.40080453
Min length	3

Characters and Unicode

Total characters	1995144
Distinct characters	179
Distinct categories	15 ?
Distinct scripts	4 ?
Distinct blocks	4 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1503 ?
Unique (%)	2.3%

Sample

1st row	Holcim (Deutschland) GmbH Werk Höver
2nd row	Stabilimento di Tavernola Bergamasca
3rd row	COMPLEJO MEDIOAMBIENTAL DE ZURITA
4th row	Elektrárny Prunéřov
5th row	TAMPEREEN VESI LIIKELAITOS, VIINIKANLAHDEN JÄTEVEDENPUHDISTAMO

Common Values

Value	Count	Frequency (%)
Enel Produzione S.p.A.	234	0.4%
SNAM Rete Gas	123	0.2%
A2A gencogas S.p.A.	112	0.2%
Trans Austria Gasleitung GmbH	109	0.2%
Versalis S.p.A.	102	0.2%
WIEN ENERGIE GmbH	84	0.1%
Edison S.p.A.	82	0.1%
Enipower S.p.A.	78	0.1%
Eni S.p.A.	73	0.1%
FERROPEM	70	0.1%
Other values (7920)	64561	98.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
	10016	3.5%
de	9554	3.4%
gmbh	5370	1.9%
s.a	3717	1.3%
di	3009	1.1%
landfill	2806	1.0%
power	2502	0.9%
sa	2070	0.7%
site	2044	0.7%
ag	1959	0.7%
Other values (11130)	240153	84.8%

Most occurring characters

Value	Count	Frequency (%)
	222354	11.1%
e	106544	5.3%
a	90352	4.5%
A	82570	4.1%
E	82479	4.1%
r	75184	3.8%
i	72557	3.6%
n	72463	3.6%
o	65985	3.3%
S	64217	3.2%
Other values (169)	1060439	53.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	924474	46.3%
Uppercase Letter	774149	38.8%
Space Separator	222354	11.1%
Other Punctuation	47366	2.4%
Dash Punctuation	12716	0.6%
Decimal Number	4997	0.3%
Open Punctuation	4420	0.2%
Close Punctuation	4382	0.2%
Math Symbol	83	< 0.1%
Final Punctuation	67	< 0.1%
Other values (5)	136	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	106544	11.5%
a	90352	9.8%
r	75184	8.1%
i	72557	7.8%
n	72463	7.8%
o	65985	7.1%
t	60070	6.5%
l	52165	5.6%
s	40492	4.4%
d	32315	3.5%
Other values (64)	256347	27.7%

Uppercase Letter

Value	Count	Frequency (%)
A	82570	10.7%
E	82479	10.7%
S	64217	8.3%
I	52578	6.8%
R	51225	6.6%
O	45097	5.8%
C	42575	5.5%
L	41748	5.4%
N	40857	5.3%
T	37921	4.9%
Other values (59)	232882	30.1%

Decimal Number

Value	Count	Frequency (%)
1	975	19.5%
3	932	18.7%
2	906	18.1%
0	557	11.1%
4	415	8.3%
9	283	5.7%
5	278	5.6%
7	254	5.1%
6	218	4.4%
8	179	3.6%

Other Punctuation

Value	Count	Frequency (%)
.	29296	61.9%
,	10595	22.4%
"	2137	4.5%
/	2129	4.5%
&	1955	4.1%
'	1155	2.4%
:	69	0.1%
@	21	< 0.1%
¿	9	< 0.1%

Open Punctuation

Value	Count	Frequency (%)
(	4398	99.5%
„	13	0.3%
‚	9	0.2%

Dash Punctuation

Value	Count	Frequency (%)
-	12644	99.4%
–	72	0.6%

Final Punctuation

Value	Count	Frequency (%)
’	52	77.6%
”	15	22.4%

Other Letter

Value	Count	Frequency (%)
º	49	89.1%
ª	6	10.9%

Modifier Symbol

Value	Count	Frequency (%)
´	31	67.4%
`	15	32.6%

Space Separator

Value	Count	Frequency (%)
	222354	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	4382	100.0%

Math Symbol

Value	Count	Frequency (%)
+	83	100.0%

Initial Punctuation

Value	Count	Frequency (%)
“	28	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	5	100.0%

Control

Value	Count	Frequency (%)
	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1698666	85.1%
Common	296466	14.9%
Cyrillic	10	< 0.1%
Greek	2	< 0.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	106544	6.3%
a	90352	5.3%
A	82570	4.9%
E	82479	4.9%
r	75184	4.4%
i	72557	4.3%
n	72463	4.3%
o	65985	3.9%
S	64217	3.8%
t	60070	3.5%
Other values (133)	926245	54.5%

Common

Value	Count	Frequency (%)
	222354	75.0%
.	29296	9.9%
-	12644	4.3%
,	10595	3.6%
(	4398	1.5%
)	4382	1.5%
"	2137	0.7%
/	2129	0.7%
&	1955	0.7%
'	1155	0.4%
Other values (24)	5421	1.8%

Cyrillic

Value	Count	Frequency (%)
І	10	100.0%

Greek

Value	Count	Frequency (%)
Ι	2	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1963710	98.4%
None	31235	1.6%
Punctuation	189	< 0.1%
Cyrillic	10	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	222354	11.3%
e	106544	5.4%
a	90352	4.6%
A	82570	4.2%
E	82479	4.2%
r	75184	3.8%
i	72557	3.7%
n	72463	3.7%
o	65985	3.4%
S	64217	3.3%
Other values (67)	1029005	52.4%

None

Value	Count	Frequency (%)
ł	3969	12.7%
ä	3393	10.9%
ó	2271	7.3%
á	2211	7.1%
É	1567	5.0%
ö	1385	4.4%
ü	1364	4.4%
Ó	1141	3.7%
í	895	2.9%
Á	868	2.8%
Other values (85)	12171	39.0%

Punctuation

Value	Count	Frequency (%)
–	72	38.1%
’	52	27.5%
“	28	14.8%
”	15	7.9%
„	13	6.9%
‚	9	4.8%

Cyrillic

Value	Count	Frequency (%)
І	10	100.0%

City
Categorical

HIGH CARDINALITY

Distinct	5136
Distinct (%)	7.8%
Missing	0
Missing (%)	0.0%
Memory size	512.8 KiB

--	1975
Antwerpen	341
Duisburg	275
Cork	220
Botlek Rotterdam	215
Other values (5131)	62602

Length

Max length	47
Median length	35
Mean length	9.377034193
Min length	1

Characters and Unicode

Total characters	615396
Distinct characters	187
Distinct categories	8 ?
Distinct scripts	3 ?
Distinct blocks	3 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	718 ?
Unique (%)	1.1%

Sample

1st row	Sehnde
2nd row	TAVERNOLA BERGAMASCA
3rd row	PUERTO DEL ROSARIO
4th row	Kadaň
5th row	Tampere

Common Values

Value	Count	Frequency (%)
--	1975	3.0%
Antwerpen	341	0.5%
Duisburg	275	0.4%
Cork	220	0.3%
Botlek Rotterdam	215	0.3%
FOS-SUR-MER	159	0.2%
Gent	156	0.2%
Hamburg	152	0.2%
Berlin	149	0.2%
Bremen	149	0.2%
Other values (5126)	61837	94.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
	2004	2.4%
de	1615	2.0%
la	832	1.0%
rotterdam	518	0.6%
san	467	0.6%
st	361	0.4%
antwerpen	342	0.4%
del	289	0.4%
duisburg	275	0.3%
am	228	0.3%
Other values (5513)	75518	91.6%

Most occurring characters

Value	Count	Frequency (%)
e	34585	5.6%
A	32191	5.2%
a	28510	4.6%
E	27421	4.5%
n	24720	4.0%
r	24680	4.0%
R	22567	3.7%
O	21544	3.5%
S	19991	3.2%
L	19640	3.2%
Other values (177)	359547	58.4%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	292753	47.6%
Lowercase Letter	289560	47.1%
Space Separator	17878	2.9%
Dash Punctuation	10431	1.7%
Other Punctuation	3271	0.5%
Open Punctuation	579	0.1%
Close Punctuation	579	0.1%
Decimal Number	345	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	34585	11.9%
a	28510	9.8%
n	24720	8.5%
r	24680	8.5%
o	18500	6.4%
i	18312	6.3%
l	15698	5.4%
t	15179	5.2%
s	13036	4.5%
d	10028	3.5%
Other values (93)	86312	29.8%

Uppercase Letter

Value	Count	Frequency (%)
A	32191	11.0%
E	27421	9.4%
R	22567	7.7%
O	21544	7.4%
S	19991	6.8%
L	19640	6.7%
N	19516	6.7%
I	18366	6.3%
T	14019	4.8%
M	10202	3.5%
Other values (56)	87296	29.8%

Decimal Number

Value	Count	Frequency (%)
1	118	34.2%
5	70	20.3%
0	43	12.5%
3	37	10.7%
2	26	7.5%
8	19	5.5%
4	17	4.9%
7	12	3.5%
6	3	0.9%

Other Punctuation

Value	Count	Frequency (%)
,	1150	35.2%
.	1089	33.3%
'	664	20.3%
/	367	11.2%
:	1	< 0.1%

Space Separator

Value	Count	Frequency (%)
	17878	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	10431	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	579	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	579	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	577369	93.8%
Common	33083	5.4%
Cyrillic	4944	0.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	34585	6.0%
A	32191	5.6%
a	28510	4.9%
E	27421	4.7%
n	24720	4.3%
r	24680	4.3%
R	22567	3.9%
O	21544	3.7%
S	19991	3.5%
L	19640	3.4%
Other values (112)	321520	55.7%

Cyrillic

Value	Count	Frequency (%)
о	634	12.8%
в	435	8.8%
и	378	7.6%
е	370	7.5%
л	299	6.0%
а	289	5.8%
р	247	5.0%
н	238	4.8%
С	148	3.0%
с	142	2.9%
Other values (37)	1764	35.7%

Common

Value	Count	Frequency (%)
	17878	54.0%
-	10431	31.5%
,	1150	3.5%
.	1089	3.3%
'	664	2.0%
(	579	1.8%
)	579	1.8%
/	367	1.1%
1	118	0.4%
5	70	0.2%
Other values (8)	158	0.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	598060	97.2%
None	12392	2.0%
Cyrillic	4944	0.8%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	34585	5.8%
A	32191	5.4%
a	28510	4.8%
E	27421	4.6%
n	24720	4.1%
r	24680	4.1%
R	22567	3.8%
O	21544	3.6%
S	19991	3.3%
L	19640	3.3%
Other values (60)	342211	57.2%

None

Value	Count	Frequency (%)
ü	1264	10.2%
ó	1016	8.2%
á	835	6.7%
ö	781	6.3%
ä	746	6.0%
ł	670	5.4%
í	634	5.1%
Ö	607	4.9%
Ä	409	3.3%
ę	361	2.9%
Other values (60)	5069	40.9%

Cyrillic

Value	Count	Frequency (%)
о	634	12.8%
в	435	8.8%
и	378	7.6%
е	370	7.5%
л	299	6.0%
а	289	5.8%
р	247	5.0%
н	238	4.8%
С	148	3.0%
с	142	2.9%
Other values (37)	1764	35.7%

targetRelease
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	512.8 KiB

AIR	65628

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	196884
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	AIR
2nd row	AIR
3rd row	AIR
4th row	AIR
5th row	AIR

Common Values

Value	Count	Frequency (%)
AIR	65628	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
air	65628	100.0%

Most occurring characters

Value	Count	Frequency (%)
A	65628	33.3%
I	65628	33.3%
R	65628	33.3%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	196884	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	65628	33.3%
I	65628	33.3%
R	65628	33.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	196884	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	65628	33.3%
I	65628	33.3%
R	65628	33.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	196884	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
A	65628	33.3%
I	65628	33.3%
R	65628	33.3%

pollutant
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	512.8 KiB

Nitrogen oxides (NOX)	25982
Carbon dioxide (CO2)	22964
Methane (CH4)	16682

Length

Max length	21
Median length	20
Mean length	18.6165661
Min length	13

Characters and Unicode

Total characters	1221768
Distinct characters	24
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Carbon dioxide (CO2)
2nd row	Nitrogen oxides (NOX)
3rd row	Methane (CH4)
4th row	Nitrogen oxides (NOX)
5th row	Methane (CH4)

Common Values

Value	Count	Frequency (%)
Nitrogen oxides (NOX)	25982	39.6%
Carbon dioxide (CO2)	22964	35.0%
Methane (CH4)	16682	25.4%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
nitrogen	25982	14.4%
oxides	25982	14.4%
nox	25982	14.4%
carbon	22964	12.7%
dioxide	22964	12.7%
co2	22964	12.7%
methane	16682	9.3%
ch4	16682	9.3%

Most occurring characters

Value	Count	Frequency (%)
	114574	9.4%
e	108292	8.9%
o	97892	8.0%
i	97892	8.0%
d	71910	5.9%
(	65628	5.4%
)	65628	5.4%
n	65628	5.4%
C	62610	5.1%
N	51964	4.3%
Other values (14)	419750	34.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	713426	58.4%
Uppercase Letter	222866	18.2%
Space Separator	114574	9.4%
Open Punctuation	65628	5.4%
Close Punctuation	65628	5.4%
Decimal Number	39646	3.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	108292	15.2%
o	97892	13.7%
i	97892	13.7%
d	71910	10.1%
n	65628	9.2%
x	48946	6.9%
r	48946	6.9%
t	42664	6.0%
a	39646	5.6%
s	25982	3.6%
Other values (3)	65628	9.2%

Uppercase Letter

Value	Count	Frequency (%)
C	62610	28.1%
N	51964	23.3%
O	48946	22.0%
X	25982	11.7%
M	16682	7.5%
H	16682	7.5%

Decimal Number

Value	Count	Frequency (%)
2	22964	57.9%
4	16682	42.1%

Space Separator

Value	Count	Frequency (%)
	114574	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	65628	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	65628	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	936292	76.6%
Common	285476	23.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	108292	11.6%
o	97892	10.5%
i	97892	10.5%
d	71910	7.7%
n	65628	7.0%
C	62610	6.7%
N	51964	5.5%
x	48946	5.2%
O	48946	5.2%
r	48946	5.2%
Other values (9)	233266	24.9%

Common

Value	Count	Frequency (%)
	114574	40.1%
(	65628	23.0%
)	65628	23.0%
2	22964	8.0%
4	16682	5.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1221768	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	114574	9.4%
e	108292	8.9%
o	97892	8.0%
i	97892	8.0%
d	71910	5.9%
(	65628	5.4%
)	65628	5.4%
n	65628	5.4%
C	62610	5.1%
N	51964	4.3%
Other values (14)	419750	34.4%

reportingYear
Real number (ℝ_≥0)

Distinct	14
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2012.935043

Minimum	2007
Maximum	2020
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	512.8 KiB

Quantile statistics

Minimum	2007
5-th percentile	2007
Q1	2010
median	2013
Q3	2016
95-th percentile	2019
Maximum	2020
Range	13
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	3.85365506
Coefficient of variation (CV)	0.001914445811
Kurtosis	-1.138349474
Mean	2012.935043
Median Absolute Deviation (MAD)	3
Skewness	0.1234551266
Sum	132104901
Variance	14.85065732
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=14)

Value	Count	Frequency (%)
2008	5361	8.2%
2010	5327	8.1%
2007	5266	8.0%
2009	5233	8.0%
2011	5151	7.8%
2012	5088	7.8%
2013	5073	7.7%
2014	4911	7.5%
2015	4706	7.2%
2016	4685	7.1%
Other values (4)	14827	22.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2007	5266	8.0%
2008	5361	8.2%
2009	5233	8.0%
2010	5327	8.1%
2011	5151	7.8%
2012	5088	7.8%
2013	5073	7.7%
2014	4911	7.5%
2015	4706	7.2%
2016	4685	7.1%

Value	Count	Frequency (%)
2020	2408	3.7%
2019	3771	5.7%
2018	3989	6.1%
2017	4659	7.1%
2016	4685	7.1%
2015	4706	7.2%
2014	4911	7.5%
2013	5073	7.7%
2012	5088	7.8%
2011	5151	7.8%

MONTH
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	12
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.489973792

Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	512.8 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	3
median	7
Q3	9
95-th percentile	12
Maximum	12
Range	11
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	3.450832526
Coefficient of variation (CV)	0.5317174825
Kurtosis	-1.217502713
Mean	6.489973792
Median Absolute Deviation (MAD)	3
Skewness	-0.001143937773
Sum	425924
Variance	11.90824512
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
8	5575	8.5%
9	5570	8.5%
2	5530	8.4%
4	5498	8.4%
1	5498	8.4%
7	5480	8.4%
3	5479	8.3%
10	5453	8.3%
12	5412	8.2%
11	5387	8.2%
Other values (2)	10746	16.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	5498	8.4%
2	5530	8.4%
3	5479	8.3%
4	5498	8.4%
5	5360	8.2%
6	5386	8.2%
7	5480	8.4%
8	5575	8.5%
9	5570	8.5%
10	5453	8.3%

Value	Count	Frequency (%)
12	5412	8.2%
11	5387	8.2%
10	5453	8.3%
9	5570	8.5%
8	5575	8.5%
7	5480	8.4%
6	5386	8.2%
5	5360	8.2%
4	5498	8.4%
3	5479	8.3%

DAY
Real number (ℝ_≥0)

Distinct	28
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	14.51720302

Minimum	1
Maximum	28
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	512.8 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	8
median	14
Q3	22
95-th percentile	27
Maximum	28
Range	27
Interquartile range (IQR)	14

Descriptive statistics

Standard deviation	8.097332136
Coefficient of variation (CV)	0.5577749463
Kurtosis	-1.208998231
Mean	14.51720302
Median Absolute Deviation (MAD)	7
Skewness	-0.006795525997
Sum	952735
Variance	65.56678772
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=28)

Value	Count	Frequency (%)
23	2472	3.8%
25	2459	3.7%
13	2448	3.7%
1	2443	3.7%
22	2431	3.7%
11	2427	3.7%
9	2396	3.7%
8	2378	3.6%
2	2372	3.6%
24	2366	3.6%
Other values (18)	41436	63.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	2443	3.7%
2	2372	3.6%
3	2338	3.6%
4	2286	3.5%
5	2281	3.5%
6	2316	3.5%
7	2259	3.4%
8	2378	3.6%
9	2396	3.7%
10	2323	3.5%

Value	Count	Frequency (%)
28	2323	3.5%
27	2330	3.6%
26	2312	3.5%
25	2459	3.7%
24	2366	3.6%
23	2472	3.8%
22	2431	3.7%
21	2303	3.5%
20	2364	3.6%
19	2245	3.4%

CONTINENT
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	512.8 KiB

EUROPE	65628

Length

Max length	6
Median length	6
Mean length	6
Min length	6

Characters and Unicode

Total characters	393768
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	EUROPE
2nd row	EUROPE
3rd row	EUROPE
4th row	EUROPE
5th row	EUROPE

Common Values

Value	Count	Frequency (%)
EUROPE	65628	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
europe	65628	100.0%

Most occurring characters

Value	Count	Frequency (%)
E	131256	33.3%
U	65628	16.7%
R	65628	16.7%
O	65628	16.7%
P	65628	16.7%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	393768	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
E	131256	33.3%
U	65628	16.7%
R	65628	16.7%
O	65628	16.7%
P	65628	16.7%

Most occurring scripts

Value	Count	Frequency (%)
Latin	393768	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
E	131256	33.3%
U	65628	16.7%
R	65628	16.7%
O	65628	16.7%
P	65628	16.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	393768	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
E	131256	33.3%
U	65628	16.7%
R	65628	16.7%
O	65628	16.7%
P	65628	16.7%

max_wind_speed
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	57060
Distinct (%)	86.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	15.51595781

Minimum	8.011957526
Maximum	22.99138212
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	512.8 KiB

Quantile statistics

Minimum	8.011957526
5-th percentile	10.36647333
Q1	13.32416598
median	15.50682018
Q3	17.71820071
95-th percentile	20.66158275
Maximum	22.99138212
Range	14.97942459
Interquartile range (IQR)	4.394034725

Descriptive statistics

Standard deviation	3.067272183
Coefficient of variation (CV)	0.1976850041
Kurtosis	-0.5914420931
Mean	15.51595781
Median Absolute Deviation (MAD)	2.198767759
Skewness	-0.003789813244
Sum	1018281.279
Variance	9.408158646
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
17.04592471	5	< 0.1%
20.66930195	5	< 0.1%
16.61384067	5	< 0.1%
18.13470913	5	< 0.1%
15.51330409	5	< 0.1%
15.54142008	5	< 0.1%
14.76777071	5	< 0.1%
11.51424447	4	< 0.1%
16.01848214	4	< 0.1%
12.52264296	4	< 0.1%
Other values (57050)	65581	99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
8.011957526	1	< 0.1%
8.06077402	1	< 0.1%
8.062689172	1	< 0.1%
8.080201144	1	< 0.1%
8.095657704	1	< 0.1%
8.096044778	1	< 0.1%
8.105868134	2	< 0.1%
8.107999203	1	< 0.1%
8.137407304	1	< 0.1%
8.146132255	1	< 0.1%

Value	Count	Frequency (%)
22.99138212	2	< 0.1%
22.94767146	1	< 0.1%
22.94683865	1	< 0.1%
22.94551394	1	< 0.1%
22.94104232	1	< 0.1%
22.94000705	1	< 0.1%
22.93081599	1	< 0.1%
22.9095764	1	< 0.1%
22.90148581	1	< 0.1%
22.8969487	1	< 0.1%

avg_wind_speed
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	57060
Distinct (%)	86.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	18.01528462

Minimum	14.00010009
Maximum	21.99997338
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	512.8 KiB

Quantile statistics

Minimum	14.00010009
5-th percentile	14.40200873
Q1	16.01219727
median	18.02078864
Q3	20.01170176
95-th percentile	21.6147175
Maximum	21.99997338
Range	7.999873293
Interquartile range (IQR)	3.999504488

Descriptive statistics

Standard deviation	2.310738906
Coefficient of variation (CV)	0.1282654676
Kurtosis	-1.197352358
Mean	18.01528462
Median Absolute Deviation (MAD)	1.998937055
Skewness	-0.003151742333
Sum	1182307.099
Variance	5.339514294
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
18.761321	5	< 0.1%
20.99478187	5	< 0.1%
19.30661389	5	< 0.1%
18.40751236	5	< 0.1%
18.66754985	5	< 0.1%
14.64372651	5	< 0.1%
20.32197552	5	< 0.1%
14.77105586	4	< 0.1%
18.72290635	4	< 0.1%
17.446596	4	< 0.1%
Other values (57050)	65581	99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
14.00010009	1	< 0.1%
14.00028742	1	< 0.1%
14.00037559	1	< 0.1%
14.00038713	1	< 0.1%
14.00039859	2	< 0.1%
14.00040384	1	< 0.1%
14.00040427	1	< 0.1%
14.00047328	1	< 0.1%
14.00063342	1	< 0.1%
14.00072678	1	< 0.1%

Value	Count	Frequency (%)
21.99997338	1	< 0.1%
21.99991947	1	< 0.1%
21.99989079	1	< 0.1%
21.99987469	4	< 0.1%
21.99956973	1	< 0.1%
21.99945553	1	< 0.1%
21.99933135	1	< 0.1%
21.99925629	1	< 0.1%
21.99879	1	< 0.1%
21.99874293	2	< 0.1%

min_wind_speed
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	57060
Distinct (%)	86.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	22.52103769

Minimum	15.03258912
Maximum	29.93360301
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	512.8 KiB

Quantile statistics

Minimum	15.03258912
5-th percentile	17.35821092
Q1	20.34615774
median	22.54038734
Q3	24.71525128
95-th percentile	27.60599227
Maximum	29.93360301
Range	14.90101389
Interquartile range (IQR)	4.369093538

Descriptive statistics

Standard deviation	3.059973017
Coefficient of variation (CV)	0.1358717595
Kurtosis	-0.5914370694
Mean	22.52103769
Median Absolute Deviation (MAD)	2.183472814
Skewness	-0.02133438631
Sum	1478010.662
Variance	9.363434865
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
19.77531341	5	< 0.1%
28.95354841	5	< 0.1%
27.26492822	5	< 0.1%
22.46879074	5	< 0.1%
20.42878547	5	< 0.1%
17.06434585	5	< 0.1%
21.45062899	5	< 0.1%
16.59222325	4	< 0.1%
25.39492534	4	< 0.1%
20.40601414	4	< 0.1%
Other values (57050)	65581	99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
15.03258912	1	< 0.1%
15.04535762	1	< 0.1%
15.05313144	1	< 0.1%
15.05564738	1	< 0.1%
15.0595347	1	< 0.1%
15.06856854	1	< 0.1%
15.08021939	2	< 0.1%
15.10168216	1	< 0.1%
15.11690061	1	< 0.1%
15.11841179	1	< 0.1%

Value	Count	Frequency (%)
29.93360301	1	< 0.1%
29.92556692	1	< 0.1%
29.91436677	2	< 0.1%
29.90658594	1	< 0.1%
29.90434173	1	< 0.1%
29.89835866	1	< 0.1%
29.8958781	1	< 0.1%
29.88896106	1	< 0.1%
29.87586267	1	< 0.1%
29.86964849	1	< 0.1%

max_temp
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	57060
Distinct (%)	86.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9.455406211

Minimum	-3.141463865
Maximum	20.93826591
Zeros	0
Zeros (%)	0.0%
Negative	2770
Negative (%)	4.2%
Memory size	512.8 KiB

Quantile statistics

Minimum	-3.141463865
5-th percentile	0.297407858
Q1	5.879820641
median	9.698967359
Q3	13.28241663
95-th percentile	17.72662713
Maximum	20.93826591
Range	24.07972977
Interquartile range (IQR)	7.402595989

Descriptive statistics

Standard deviation	5.21652464
Coefficient of variation (CV)	0.551697571
Kurtosis	-0.6679210534
Mean	9.455406211
Median Absolute Deviation (MAD)	3.686128408
Skewness	-0.1703014119
Sum	620539.3988
Variance	27.21212932
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10.21924166	5	< 0.1%
4.884347717	5	< 0.1%
12.69703122	5	< 0.1%
1.595268523	5	< 0.1%
6.864678111	5	< 0.1%
5.265424175	5	< 0.1%
2.795245735	5	< 0.1%
8.608741263	4	< 0.1%
11.38831078	4	< 0.1%
12.55174191	4	< 0.1%
Other values (57050)	65581	99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-3.141463865	2	< 0.1%
-3.075562621	1	< 0.1%
-3.071525209	1	< 0.1%
-3.041452495	2	< 0.1%
-3.033178012	1	< 0.1%
-2.957447236	1	< 0.1%
-2.947022823	1	< 0.1%
-2.93982001	1	< 0.1%
-2.939164723	1	< 0.1%
-2.92891221	1	< 0.1%

Value	Count	Frequency (%)
20.93826591	1	< 0.1%
20.92611588	1	< 0.1%
20.85588499	1	< 0.1%
20.85557011	1	< 0.1%
20.84754357	2	< 0.1%
20.84356455	3	< 0.1%
20.84062925	1	< 0.1%
20.83720876	3	< 0.1%
20.8243353	1	< 0.1%
20.81953963	1	< 0.1%

avg_temp
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	57060
Distinct (%)	86.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	10.44814151

Minimum	-0.1991759675
Maximum	19.99940286
Zeros	0
Zeros (%)	0.0%
Negative	387
Negative (%)	0.6%
Memory size	512.8 KiB

Quantile statistics

Minimum	-0.1991759675
5-th percentile	1.310303447
Q1	7.186013308
median	10.70150351
Q3	14.19357768
95-th percentile	18.68819061
Maximum	19.99940286
Range	20.19857883
Interquartile range (IQR)	7.007564371

Descriptive statistics

Standard deviation	5.084528995
Coefficient of variation (CV)	0.486644346
Kurtosis	-0.7281556885
Mean	10.44814151
Median Absolute Deviation (MAD)	3.502796436
Skewness	-0.1871286859
Sum	685690.6313
Variance	25.8524351
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
13.17967145	5	< 0.1%
7.530973596	5	< 0.1%
12.48903048	5	< 0.1%
3.525724243	5	< 0.1%
7.555133845	5	< 0.1%
6.001729848	5	< 0.1%
1.997484439	5	< 0.1%
8.369606079	4	< 0.1%
10.39451944	4	< 0.1%
12.54174356	4	< 0.1%
Other values (57050)	65581	99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-0.1991759675	2	< 0.1%
-0.1986566594	1	< 0.1%
-0.198573916	1	< 0.1%
-0.1979472568	1	< 0.1%
-0.1956317355	1	< 0.1%
-0.1950297157	1	< 0.1%
-0.1943625907	1	< 0.1%
-0.1943099303	1	< 0.1%
-0.193819056	1	< 0.1%
-0.193703916	1	< 0.1%

Value	Count	Frequency (%)
19.99940286	2	< 0.1%
19.99934257	1	< 0.1%
19.99871025	1	< 0.1%
19.99864512	1	< 0.1%
19.99858787	1	< 0.1%
19.99852063	1	< 0.1%
19.99847884	1	< 0.1%
19.99833936	1	< 0.1%
19.99767701	1	< 0.1%
19.99762672	1	< 0.1%

min_temp
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct	57060
Distinct (%)	86.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	13.44282711

Minimum	0.8948269078
Maximum	24.902108
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	512.8 KiB

Quantile statistics

Minimum	0.8948269078
5-th percentile	4.235785504
Q1	9.894280935
median	13.69247276
Q3	17.26799999
95-th percentile	21.73600314
Maximum	24.902108
Range	24.00728109
Interquartile range (IQR)	7.373719057

Descriptive statistics

Standard deviation	5.216068445
Coefficient of variation (CV)	0.3880187109
Kurtosis	-0.6577840946
Mean	13.44282711
Median Absolute Deviation (MAD)	3.678393887
Skewness	-0.1704416031
Sum	882225.8573
Variance	27.20737002
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
14.21888806	5	< 0.1%
10.81834522	5	< 0.1%
16.00170596	5	< 0.1%
6.242928589	5	< 0.1%
9.9316052	5	< 0.1%
7.851481986	5	< 0.1%
5.326421358	5	< 0.1%
11.45946965	4	< 0.1%
14.72035813	4	< 0.1%
14.74798104	4	< 0.1%
Other values (57050)	65581	99.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.8948269078	1	< 0.1%
0.8959521782	1	< 0.1%
0.9507770814	1	< 0.1%
0.9952731205	1	< 0.1%
0.9999267043	2	< 0.1%
1.003606393	1	< 0.1%
1.009808228	1	< 0.1%
1.011517201	1	< 0.1%
1.021968087	1	< 0.1%
1.033683523	1	< 0.1%

Value	Count	Frequency (%)
24.902108	1	< 0.1%
24.88484211	1	< 0.1%
24.85542506	1	< 0.1%
24.84893262	1	< 0.1%
24.8406712	1	< 0.1%
24.82579329	1	< 0.1%
24.82537293	1	< 0.1%
24.82061335	1	< 0.1%
24.81779182	1	< 0.1%
24.81278873	2	< 0.1%

DAY WITH FOGS
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	20
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.232568416

Minimum	0
Maximum	19
Zeros	18771
Zeros (%)	28.6%
Negative	0
Negative (%)	0.0%
Memory size	512.8 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	2
95-th percentile	12
Maximum	19
Range	19
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	3.778428507
Coefficient of variation (CV)	1.692413312
Kurtosis	7.946473712
Mean	2.232568416
Median Absolute Deviation (MAD)	1
Skewness	2.909564205
Sum	146519
Variance	14.27652198
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=20)

Value	Count	Frequency (%)
1	19524	29.7%
2	19286	29.4%
0	18771	28.6%
11	522	0.8%
5	512	0.8%
18	509	0.8%
15	501	0.8%
4	493	0.8%
3	483	0.7%
12	481	0.7%
Other values (10)	4546	6.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	18771	28.6%
1	19524	29.7%
2	19286	29.4%
3	483	0.7%
4	493	0.8%
5	512	0.8%
6	445	0.7%
7	434	0.7%
8	467	0.7%
9	478	0.7%

Value	Count	Frequency (%)
19	478	0.7%
18	509	0.8%
17	446	0.7%
16	469	0.7%
15	501	0.8%
14	470	0.7%
13	389	0.6%
12	481	0.7%
11	522	0.8%
10	470	0.7%

REPORTER NAME
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	45016
Distinct (%)	68.6%
Missing	0
Missing (%)	0.0%
Memory size	512.8 KiB

Michael Brown	25
James Smith	25
Michael Smith	23
Michael Williams	22
Robert Jones	22
Other values (45011)	65511

Length

Max length	28
Median length	26
Mean length	13.27245993
Min length	6

Characters and Unicode

Total characters	871045
Distinct characters	54
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	32940 ?
Unique (%)	50.2%

Sample

1st row	Mr. Jacob Ortega
2nd row	Ashlee Serrano
3rd row	Vincent Kemp
4th row	Carol Gray
5th row	Blake Ford

Common Values

Value	Count	Frequency (%)
Michael Brown	25	< 0.1%
James Smith	25	< 0.1%
Michael Smith	23	< 0.1%
Michael Williams	22	< 0.1%
Robert Jones	22	< 0.1%
Christopher Smith	20	< 0.1%
Christopher Johnson	20	< 0.1%
Jessica Smith	19	< 0.1%
Jennifer Johnson	19	< 0.1%
Jennifer Smith	19	< 0.1%
Other values (45006)	65414	99.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
michael	1467	1.1%
smith	1349	1.0%
johnson	1158	0.9%
james	1093	0.8%
david	973	0.7%
john	958	0.7%
christopher	953	0.7%
williams	916	0.7%
robert	907	0.7%
jennifer	905	0.7%
Other values (1588)	123554	92.0%

Most occurring characters

Value	Count	Frequency (%)
e	80647	9.3%
a	80455	9.2%
	68605	7.9%
n	64959	7.5%
r	63053	7.2%
i	52172	6.0%
o	47478	5.5%
l	44225	5.1%
s	39163	4.5%
t	30171	3.5%
Other values (44)	300117	34.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	664657	76.3%
Uppercase Letter	136382	15.7%
Space Separator	68605	7.9%
Other Punctuation	1401	0.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	80647	12.1%
a	80455	12.1%
n	64959	9.8%
r	63053	9.5%
i	52172	7.8%
o	47478	7.1%
l	44225	6.7%
s	39163	5.9%
t	30171	4.5%
h	29258	4.4%
Other values (16)	133076	20.0%

Uppercase Letter

Value	Count	Frequency (%)
M	15107	11.1%
J	13561	9.9%
S	11097	8.1%
C	10168	7.5%
D	9133	6.7%
R	8472	6.2%
B	8438	6.2%
A	8390	6.2%
W	6439	4.7%
H	6108	4.5%
Other values (16)	39469	28.9%

Space Separator

Value	Count	Frequency (%)
	68605	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	1401	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	801039	92.0%
Common	70006	8.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	80647	10.1%
a	80455	10.0%
n	64959	8.1%
r	63053	7.9%
i	52172	6.5%
o	47478	5.9%
l	44225	5.5%
s	39163	4.9%
t	30171	3.8%
h	29258	3.7%
Other values (42)	269458	33.6%

Common

Value	Count	Frequency (%)
	68605	98.0%
.	1401	2.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	871045	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	80647	9.3%
a	80455	9.2%
	68605	7.9%
n	64959	7.5%
r	63053	7.2%
i	52172	6.0%
o	47478	5.5%
l	44225	5.1%
s	39163	4.5%
t	30171	3.5%
Other values (44)	300117	34.5%

CITY ID
Categorical

HIGH CARDINALITY

Distinct	5136
Distinct (%)	7.8%
Missing	0
Missing (%)	0.0%
Memory size	512.8 KiB

cfab1ba8c67c7c838db98d666f02a132	1975
aed13ea855ff8b71cd5ceb869fe744c1	341
f53da95e5700ca1e7d12b7a833d62663	275
002c887b8369e59e6f58a5d06a8d0817	220
0759b751086c80f98aa59e11e6a115b4	215
Other values (5131)	62602

Length

Max length	32
Median length	32
Mean length	32
Min length	32

Characters and Unicode

Total characters	2100096
Distinct characters	16
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	718 ?
Unique (%)	1.1%

Sample

1st row	7cdb5e74adcb2ffaa21c1b61395a984f
2nd row	cd1dbabbdba230b828c657a9b19a8963
3rd row	5011e3fa1436d15b34f1287f312fbada
4th row	37a6d7a71c4f7c2469e4f01b70dd90c2
5th row	471fe554e1c62d1b01cc8e4e5076c61a

Common Values

Value	Count	Frequency (%)
cfab1ba8c67c7c838db98d666f02a132	1975	3.0%
aed13ea855ff8b71cd5ceb869fe744c1	341	0.5%
f53da95e5700ca1e7d12b7a833d62663	275	0.4%
002c887b8369e59e6f58a5d06a8d0817	220	0.3%
0759b751086c80f98aa59e11e6a115b4	215	0.3%
8dc3d6c792dfa6e7eb4c59921e6c635a	159	0.2%
bc1f8a8dc753022dcebc810482590fdd	156	0.2%
35d7df6ed3d93be2927d14acc5f1fc9a	152	0.2%
ee1611b61f5688e70c12b40684dbb395	149	0.2%
92c1f80a07ad537ddb7e00137d6a25f9	149	0.2%
Other values (5126)	61837	94.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
cfab1ba8c67c7c838db98d666f02a132	1975	3.0%
aed13ea855ff8b71cd5ceb869fe744c1	341	0.5%
f53da95e5700ca1e7d12b7a833d62663	275	0.4%
002c887b8369e59e6f58a5d06a8d0817	220	0.3%
0759b751086c80f98aa59e11e6a115b4	215	0.3%
8dc3d6c792dfa6e7eb4c59921e6c635a	159	0.2%
bc1f8a8dc753022dcebc810482590fdd	156	0.2%
35d7df6ed3d93be2927d14acc5f1fc9a	152	0.2%
92c1f80a07ad537ddb7e00137d6a25f9	149	0.2%
ee1611b61f5688e70c12b40684dbb395	149	0.2%
Other values (5126)	61837	94.2%

Most occurring characters

Value	Count	Frequency (%)
6	134944	6.4%
d	134213	6.4%
b	133398	6.4%
2	133360	6.4%
c	133359	6.4%
0	132658	6.3%
8	132592	6.3%
f	132408	6.3%
a	132324	6.3%
7	131442	6.3%
Other values (6)	769398	36.6%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1306393	62.2%
Lowercase Letter	793703	37.8%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
6	134944	10.3%
2	133360	10.2%
0	132658	10.2%
8	132592	10.1%
7	131442	10.1%
1	130328	10.0%
5	129247	9.9%
3	129203	9.9%
4	126892	9.7%
9	125727	9.6%

Lowercase Letter

Value	Count	Frequency (%)
d	134213	16.9%
b	133398	16.8%
c	133359	16.8%
f	132408	16.7%
a	132324	16.7%
e	128001	16.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	1306393	62.2%
Latin	793703	37.8%

Most frequent character per script

Common

Value	Count	Frequency (%)
6	134944	10.3%
2	133360	10.2%
0	132658	10.2%
8	132592	10.1%
7	131442	10.1%
1	130328	10.0%
5	129247	9.9%
3	129203	9.9%
4	126892	9.7%
9	125727	9.6%

Latin

Value	Count	Frequency (%)
d	134213	16.9%
b	133398	16.8%
c	133359	16.8%
f	132408	16.7%
a	132324	16.7%
e	128001	16.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2100096	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
6	134944	6.4%
d	134213	6.4%
b	133398	6.4%
2	133360	6.4%
c	133359	6.4%
0	132658	6.3%
8	132592	6.3%
f	132408	6.3%
a	132324	6.3%
7	131442	6.3%
Other values (6)	769398	36.6%

EPRTRAnnexIMainActivityCode
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION

Distinct	70
Distinct (%)	0.1%
Missing	2
Missing (%)	< 0.1%
Memory size	512.8 KiB

1(c)	21527
5(d)	10452
5(b)	3454
3(c)(i)	3300
3(e)	2725
Other values (65)	24168

Length

Max length	10
Median length	4
Mean length	4.551900162
Min length	4

Characters and Unicode

Total characters	298723
Distinct characters	21
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3(c)(i)
2nd row	3(c)
3rd row	5(d)
4th row	1(c)
5th row	5(f)

Common Values

Value	Count	Frequency (%)
1(c)	21527	32.8%
5(d)	10452	15.9%
5(b)	3454	5.3%
3(c)(i)	3300	5.0%
3(e)	2725	4.2%
1(a)	2454	3.7%
6(b)	2416	3.7%
3(c)	1519	2.3%
2(b)	1461	2.2%
6(a)	1395	2.1%
Other values (60)	14923	22.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
1(c	21527	32.8%
5(d	10452	15.9%
5(b	3454	5.3%
3(c)(i	3300	5.0%
3(e	2725	4.2%
1(a	2454	3.7%
6(b	2416	3.7%
3(c	1519	2.3%
2(b	1461	2.2%
6(a	1395	2.1%
Other values (60)	14923	22.7%

Most occurring characters

Value	Count	Frequency (%)
)	75521	25.3%
(	75521	25.3%
c	29180	9.8%
1	24562	8.2%
5	15889	5.3%
i	15339	5.1%
d	10948	3.7%
a	10545	3.5%
3	10188	3.4%
b	10034	3.4%
Other values (11)	20996	7.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	82055	27.5%
Close Punctuation	75521	25.3%
Open Punctuation	75521	25.3%
Decimal Number	65626	22.0%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
c	29180	35.6%
i	15339	18.7%
d	10948	13.3%
a	10545	12.9%
b	10034	12.2%
e	3884	4.7%
v	964	1.2%
f	616	0.8%
g	419	0.5%
x	126	0.2%

Decimal Number

Value	Count	Frequency (%)
1	24562	37.4%
5	15889	24.2%
3	10188	15.5%
4	4332	6.6%
6	3817	5.8%
2	3154	4.8%
7	2144	3.3%
8	1305	2.0%
9	235	0.4%

Close Punctuation

Value	Count	Frequency (%)
)	75521	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	75521	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	216668	72.5%
Latin	82055	27.5%

Most frequent character per script

Common

Value	Count	Frequency (%)
)	75521	34.9%
(	75521	34.9%
1	24562	11.3%
5	15889	7.3%
3	10188	4.7%
4	4332	2.0%
6	3817	1.8%
2	3154	1.5%
7	2144	1.0%
8	1305	0.6%

Latin

Value	Count	Frequency (%)
c	29180	35.6%
i	15339	18.7%
d	10948	13.3%
a	10545	12.9%
b	10034	12.2%
e	3884	4.7%
v	964	1.2%
f	616	0.8%
g	419	0.5%
x	126	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	298723	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
)	75521	25.3%
(	75521	25.3%
c	29180	9.8%
1	24562	8.2%
5	15889	5.3%
i	15339	5.1%
d	10948	3.7%
a	10545	3.5%
3	10188	3.4%
b	10034	3.4%
Other values (11)	20996	7.0%

EPRTRSectorCode
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	9
Distinct (%)	< 0.1%
Missing	2
Missing (%)	< 0.1%
Infinite	0
Infinite (%)	0.0%
Mean	3.179715357

Minimum	1
Maximum	9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	512.8 KiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	3
Q3	5
95-th percentile	7
Maximum	9
Range	8
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.054170901
Coefficient of variation (CV)	0.6460235179
Kurtosis	-0.9379714527
Mean	3.179715357
Median Absolute Deviation (MAD)	2
Skewness	0.4153893295
Sum	208672
Variance	4.219618089
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
1	24562	37.4%
5	15889	24.2%
3	10188	15.5%
4	4332	6.6%
6	3817	5.8%
2	3154	4.8%
7	2144	3.3%
8	1305	2.0%
9	235	0.4%
(Missing)	2	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	24562	37.4%
2	3154	4.8%
3	10188	15.5%
4	4332	6.6%
5	15889	24.2%
6	3817	5.8%
7	2144	3.3%
8	1305	2.0%
9	235	0.4%

Value	Count	Frequency (%)
9	235	0.4%
8	1305	2.0%
7	2144	3.3%
6	3817	5.8%
5	15889	24.2%
4	4332	6.6%
3	10188	15.5%
2	3154	4.8%
1	24562	37.4%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	df_index	countryName	eprtrSectorName	EPRTRAnnexIMainActivityLabel	FacilityInspireID	facilityName	City	targetRelease	pollutant	reportingYear	MONTH	DAY	CONTINENT	max_wind_speed	avg_wind_speed	min_wind_speed	max_temp	avg_temp	min_temp	DAY WITH FOGS	REPORTER NAME	CITY ID	EPRTRAnnexIMainActivityCode	EPRTRSectorCode
0	0	Germany	Mineral industry	Installations for the production of cement clinker in rotary kilns	https://registry.gdi-de.org/id/de.ni.mu/06221720040	Holcim (Deutschland) GmbH Werk Höver	Sehnde	AIR	Carbon dioxide (CO2)	2015	10	20	EUROPE	15.118767	14.312541	21.419106	2.864895	4.924169	9.688206	2	Mr. Jacob Ortega	7cdb5e74adcb2ffaa21c1b61395a984f	3(c)(i)	3
1	1	Italy	Mineral industry	Installations for the production of cement clinker in rotary kilns, lime in rotary kilns, cement or lime in other furnaces. Note to reporters, use Level 3 activity e.g. 3(c)(i), in preference to 3(c). Level 2 activity class (i.e. 3(c)) only to be used where Level 3 is not available.	IT.CAED/240602021.FACILITY	Stabilimento di Tavernola Bergamasca	TAVERNOLA BERGAMASCA	AIR	Nitrogen oxides (NOX)	2018	9	21	EUROPE	19.661550	19.368166	21.756389	5.462839	7.864403	12.023521	1	Ashlee Serrano	cd1dbabbdba230b828c657a9b19a8963	3(c)	3
2	2	Spain	Waste and wastewater management	Landfills (excluding landfills of inert waste and landfills, which were definitely closed before 16.7.2001 or for which the after-care phase required by the competent authorities according to Article 13 of Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste has expired)	ES.CAED/001966000.FACILITY	COMPLEJO MEDIOAMBIENTAL DE ZURITA	PUERTO DEL ROSARIO	AIR	Methane (CH4)	2019	2	4	EUROPE	12.729453	14.701985	17.103930	1.511201	4.233438	8.632193	2	Vincent Kemp	5011e3fa1436d15b34f1287f312fbada	5(d)	5
3	3	Czechia	Energy sector	Thermal power stations and other combustion installations	CZ.MZP.U422/CZ34736841.FACILITY	Elektrárny Prunéřov	Kadaň	AIR	Nitrogen oxides (NOX)	2012	8	6	EUROPE	11.856417	16.122584	17.537184	10.970301	10.298348	15.179215	0	Carol Gray	37a6d7a71c4f7c2469e4f01b70dd90c2	1(c)	1
4	4	Finland	Waste and wastewater management	Urban waste-water treatment plants	http://paikkatiedot.fi/so/1002031/pf/ProductionFacility/0000000928.ProductionFacility	TAMPEREEN VESI LIIKELAITOS, VIINIKANLAHDEN JÄTEVEDENPUHDISTAMO	Tampere	AIR	Methane (CH4)	2018	12	22	EUROPE	17.111930	20.201604	21.536012	11.772039	11.344078	16.039004	2	Blake Ford	471fe554e1c62d1b01cc8e4e5076c61a	5(f)	5
5	5	Switzerland	Energy sector	Mineral oil and gas refineries	CH.CAED/000000011.Facility	Varo Refining Cressier SA / Raffinerie de Cressier	Cressier	AIR	Nitrogen oxides (NOX)	2009	11	26	EUROPE	13.610384	16.054021	18.476185	0.218463	1.695830	3.081757	2	Jonathan Evans	9ecac1661f9a6d2ea27ea6582db34d9f	1(a)	1
6	6	France	Mineral industry	Installations for the manufacture of glass, including glass fibre	FR.CAED/11626.FACILITY	VERALLIA	COGNAC	AIR	Carbon dioxide (CO2)	2008	5	5	EUROPE	12.816569	15.940397	21.873807	10.954453	13.806014	16.682482	1	Kara Martin	1eb1fba9d2767e70c428514f7299acc0	3(e)	3
7	7	Poland	Paper and wood production and processing	Industrial plants for the production of paper and board and other primary wood products (such as chipboard, fibreboard and plywood)	PL.MŚ/000000138.FACILITY	Arctic Paper Kostrzyn S.A.	Kostrzyn nad Odrą	AIR	Carbon dioxide (CO2)	2011	4	11	EUROPE	9.143964	14.174349	19.879915	11.915887	12.930775	17.699905	2	David Nichols	90ada31eb6075ca41d9e7b23d27b1526	6(b)	6
8	8	United Kingdom	Energy sector	Thermal power stations and other combustion installations	UK.CAED/BEISOffsh-Bleo-Holm.FACILITY	Bleo Holm FPSO	--	AIR	Carbon dioxide (CO2)	2010	6	20	EUROPE	20.766119	21.205965	26.255209	6.348797	7.877442	11.130713	17	Frederick Chapman	cfab1ba8c67c7c838db98d666f02a132	1(c)	1
9	9	France	Chemical industry	Chemical installations for the production on an industrial scale of basic organic chemicals: Simple hydrocarbons (linear or cyclic, saturated or unsaturated, aliphatic or aromatic)	FR.CAED/3839.FACILITY	USINE DE GONFREVILLE	GONFREVILLE-L'ORCHER	AIR	Carbon dioxide (CO2)	2014	11	13	EUROPE	17.949222	20.947898	27.992034	9.633089	10.736422	12.305046	0	Sheena Conner	bf61dcbfc9487dc9dd63e8100d0b057e	4(a)(i)	4

Last rows

	df_index	countryName	eprtrSectorName	EPRTRAnnexIMainActivityLabel	FacilityInspireID	facilityName	City	targetRelease	pollutant	reportingYear	MONTH	DAY	CONTINENT	max_wind_speed	avg_wind_speed	min_wind_speed	max_temp	avg_temp	min_temp	DAY WITH FOGS	REPORTER NAME	CITY ID	EPRTRAnnexIMainActivityCode	EPRTRSectorCode
65618	18066	France	Energy sector	Thermal power stations and other combustion installations	FR.CAED/12044.FACILITY	EDF PRODUCTION ELECTRIQUE INSULAIRE - ETABLISSEMENT DE HAUTE CORSE	LUCCIANA	AIR	Nitrogen oxides (NOX)	2016	5	24	EUROPE	12.098650	17.018423	23.973918	17.980697	19.247893	22.781276	0	Kimberly Taylor	495a606d3f1402613349b0c95d35d931	1(c)	1
65619	42629	Italy	Waste and wastewater management	Landfills (excluding landfills of inert waste and landfills, which were definitely closed before 16.7.2001 or for which the after-care phase required by the competent authorities according to Article 13 of Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste has expired)	IT.EEA/104.FACILITY	Discarica di Barengo (NO)	BARENGO	AIR	Methane (CH4)	2017	2	26	EUROPE	18.431998	20.528478	26.140398	8.145384	8.357491	10.096647	0	Colin Hammond	7e0cee13d05d1d0ea4ca0973fcc1bf7d	5(d)	5
65620	11953	France	Mineral industry	Installations for the manufacture of glass, including glass fibre	FR.CAED/10710.FACILITY	ARC FRANCE - SITE D'ARQUES	ARQUES	AIR	Carbon dioxide (CO2)	2007	12	17	EUROPE	14.328479	19.974901	25.638929	2.744428	2.634764	5.252293	1	Madison Jackson	45f325609b3242ae51996742cacb606e	3(e)	3
65621	42042	Italy	Waste and wastewater management	Landfills (excluding landfills of inert waste and landfills, which were definitely closed before 16.7.2001 or for which the after-care phase required by the competent authorities according to Article 13 of Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste has expired)	IT.EEA/115315.FACILITY	MANDURIAMBIENTE S.p.A.	MANDURIA	AIR	Methane (CH4)	2016	10	23	EUROPE	16.412310	17.421044	19.317722	11.321086	13.729427	16.232119	0	Kimberly Scott	3d508ddbc66ac3b45f01e5c7b191619e	5(d)	5
65622	56922	Serbia	Chemical industry	Chemical installations for the production on an industrial scale of basic organic chemicals: Oxygen-containing hydrocarbons such as alcohols, aldehydes, ketones, carboxylic acids, esters, acetates, ethers, peroxides, epoxy resins	RS.SEPA.NRIZ/FACILITY.000000116	MSK postrojenje	Kikinda	AIR	Nitrogen oxides (NOX)	2019	8	11	EUROPE	15.719701	16.408202	22.311666	10.650435	11.022683	15.825824	2	Francisco Wilson	ffdce8563b060038d08b880c452d042e	4(a)(ii)	4
65623	5147	Cyprus	Energy sector	Thermal power stations and other combustion installations	CY.CAED/0030030000.FACILITY	Electricity Authority of Cyprus, Vassilikos Power Station	LARNAKA	AIR	Carbon dioxide (CO2)	2008	1	1	EUROPE	13.475988	18.556476	22.852530	13.345801	12.410783	17.148327	0	Tammy Faulkner	2d4776365b33d5f1be53ea4606e2c79c	1(c)	1
65624	9442	Finland	Energy sector	Thermal power stations and other combustion installations	http://paikkatiedot.fi/so/1002031/pf/ProductionFacility/0000001728.ProductionFacility	Turun Seudun Energiantuotanto Oy, Naantalin voimalaitos	Naantali	AIR	Nitrogen oxides (NOX)	2008	12	19	EUROPE	8.815939	14.461703	20.553781	3.820281	3.763833	5.657107	0	Dr. Courtney Bryant	020b11bf06b96aae1dd910a56674a8aa	1(c)	1
65625	57189	Slovenia	Waste and wastewater management	Landfills (excluding landfills of inert waste and landfills, which were definitely closed before 16.7.2001 or for which the after-care phase required by the competent authorities according to Article 13 of Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste has expired)	SI.ARSO/000000037.FACILITY	Javne službe Ptuj, Odlagališče nenevarnih odpadkov Gajke	Ptuj	AIR	Methane (CH4)	2010	8	10	EUROPE	14.793298	16.688049	20.411498	17.285365	18.349798	21.538441	2	William Greer	84afdc8367dfd9124e8b8f994e986fe9	5(d)	5
65626	40953	Italy	Mineral industry	Underground mining and related operations	IT.CAED/850592002.FACILITY	Centro Olio Val d'Agri	VIGGIANO	AIR	Nitrogen oxides (NOX)	2014	1	25	EUROPE	14.911317	16.144091	22.647192	6.387199	6.176238	9.269076	0	Leonard Roberts	09ad69bcf41256f40be3314a33e0438c	3(a)	3
65627	71260	United Kingdom	Energy sector	Thermal power stations and other combustion installations	GB.EEA/13394.FACILITY	SSE Generation Ltd, Weston Point Salt Works CHP Pant	Runcorn	AIR	Carbon dioxide (CO2)	2008	7	23	EUROPE	21.761812	21.296949	29.248276	8.220678	11.194308	14.171780	13	Mr. Benjamin Park	b5f44c55c14c881ea21499a32fc972d0	1(c)	1

Most frequently occurring

	countryName	eprtrSectorName	EPRTRAnnexIMainActivityLabel	FacilityInspireID	facilityName	City	targetRelease	pollutant	reportingYear	MONTH	DAY	CONTINENT	max_wind_speed	avg_wind_speed	min_wind_speed	max_temp	avg_temp	min_temp	DAY WITH FOGS	REPORTER NAME	CITY ID	EPRTRAnnexIMainActivityCode	EPRTRSectorCode	# duplicates
212	Belgium	Chemical industry	Chemical installations for the production on an industrial scale of basic organic chemicals: Simple hydrocarbons (linear or cyclic, saturated or unsaturated, aliphatic or aromatic)	https://data.ied_registry.omgeving.vlaanderen.be/id/productionfacility//BE.VL.000000067.FACILITY	BASF ANTWERPEN	Antwerpen	AIR	Nitrogen oxides (NOX)	2017	11	28	EUROPE	14.767771	20.321976	21.450629	2.795246	1.997484	5.326421	2	Jonathan Dawson	aed13ea855ff8b71cd5ceb869fe744c1	4(a)(i)	4	5
2882	Germany	Waste and wastewater management	Landfills (excluding landfills of inert waste and landfills, which were definitely closed before 16.7.2001 or for which the after-care phase required by the competent authorities according to Article 13 of Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste has expired)	DE.EEA/43255.FACILITY	Kreismülldeponie Hattorf am Harz	Hattorf	AIR	Methane (CH4)	2013	12	23	EUROPE	20.669302	20.994782	28.953548	4.884348	7.530974	10.818345	0	Ruth Nichols	5ec132e7607c7236c6637865b567b812	5(d)	5	5
3694	Italy	Intensive livestock production and aquaculture	Installations for the intensive rearing of poultry or pigs. Note to reporters, use Level 3 activity e.g. 7(a)(ii), in preference to 7(a). Level 2 activity class (i.e. 7(a)) only to be used where Level 3 is not available.	IT.CAED/560402001.FACILITY	Torre a Cenaia Soc. Agr. srl	CRESPINA LORENZANA	AIR	Methane (CH4)	2017	9	10	EUROPE	18.134709	18.407512	22.468791	1.595269	3.525724	6.242929	2	Jeffrey Sanchez	a997edd7e5658a6ca2e8c59b960e8859	7(a)	7	5
5080	Romania	Energy sector	Thermal power stations and other combustion installations	RO.CAED/101VL0001.FACILITY	SC CET GOVORA SA	RAMNICU VALCEA	AIR	Nitrogen oxides (NOX)	2009	6	13	EUROPE	16.613841	19.306614	27.264928	12.697031	12.489030	16.001706	2	Matthew Rubio DVM	7443dc1372eebc031dfea6ef5b9a9344	1(c)	1	5
5180	Romania	Mineral industry	Underground mining and related operations	RO.CAED/105HD0001.FACILITY	SCEH S.A , Sucursala Divizia Miniera S.A, Punct de lucru E.M.Vulcan	Vulcan	AIR	Methane (CH4)	2017	2	9	EUROPE	15.541420	14.643727	17.064346	5.265424	6.001730	7.851482	2	Natasha Jones	ba0bac8dc3def974576d783dea0f5384	3(a)	3	5
6531	United Kingdom	Energy sector	Thermal power stations and other combustion installations	UK.CAED/BEISOffsh-Alba-Northern.FACILITY	Alba Northern	--	AIR	Carbon dioxide (CO2)	2014	8	28	EUROPE	17.045925	18.761321	19.775313	10.219242	13.179671	14.218888	4	Christopher Little	cfab1ba8c67c7c838db98d666f02a132	1(c)	1	5
7259	United Kingdom	Waste and wastewater management	Landfills (excluding landfills of inert waste and landfills, which were definitely closed before 16.7.2001 or for which the after-care phase required by the competent authorities according to Article 13 of Council Directive 1999/31/EC of 26 April 1999 on the landfill of waste has expired)	UK.CAED/EW_EA-2907.FACILITY	Staple Quarry Landfill	Staple	AIR	Methane (CH4)	2012	8	25	EUROPE	15.513304	18.667550	20.428785	6.864678	7.555134	9.931605	11	Isaac Barrett	2237e275b33fc04c6968575d571f9bf5	5(d)	5	5
11	Austria	Energy sector	Mineral oil and gas refineries	AT.CAED/9008390481905.FACILITY	OMV Austria Exploration u. Production	Aderklaa	AIR	Carbon dioxide (CO2)	2019	2	9	EUROPE	17.844454	18.030750	23.899717	11.898362	13.766943	18.349999	1	Michael Perry	a784bdfb9ebb719589cc5e3cbf825cac	1(a)	1	4
105	Austria	Paper and wood production and processing	Industrial plants for the production of paper and board and other primary wood products (such as chipboard, fibreboard and plywood)	AT.CAED/9008391215714.FACILITY	W. Hamburger GmbH	Pitten	AIR	Nitrogen oxides (NOX)	2012	2	28	EUROPE	12.913523	18.030439	23.694727	11.299433	11.756286	15.701519	1	Kellie Carlson	d7e7a3891aef3c09a84556972f1edc1e	6(b)	6	4
119	Austria	Production and processing of metals	Installations for the production of pig iron or steel (primary or secondary melting) including continuous casting	AT.EEA/5868.FACILITY	voestalpine Stahl GmbH	Linz	AIR	Nitrogen oxides (NOX)	2013	11	3	EUROPE	13.950280	16.663296	19.052091	3.911315	5.176813	7.986721	0	Mark Rodriguez	443befbacdaa99c161dd11495b82b99b	2(b)	2	4

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Decimal Number

Other Punctuation

Space Separator

Open Punctuation

Close Punctuation

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Lowercase Letter

Decimal Number

Other Punctuation

Dash Punctuation

Connector Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

None

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Decimal Number